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https://pytorch.org/executorch/
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build error when generate llama2 exe file in x86 computer #6431

Open l2002924700 opened 1 week ago

l2002924700 commented 1 week ago

🐛 Describe the bug

when I prepare a llama2 exe file as https://github.com/pytorch/executorch/blob/main/examples/models/llama/README.md#step-4-run-on-your-computer-to-validate description, however there are some issues. The description is as follow:

cmake --build cmake-out/examples/models/llama2 -j16 --config Release /usr/bin/ld: cannot find -lcpublas: No such file or directory /usr/bin/ld: cannot find -leigen_blas: No such file or directory collect2: error: ld returned 1 exit status

how can I fix the issue? Thank you very much in advanced.

Versions

cmake --build cmake-out/examples/models/llama2 -j16 --config Release /usr/bin/ld: cannot find -lcpublas: No such file or directory /usr/bin/ld: cannot find -leigen_blas: No such file or directory collect2: error: ld returned 1 exit status

dbort commented 1 week ago

Hi @l2002924700, thank you for reporting this issue. To help us out, could you please run this script to give us more information about your system?

curl -O https://raw.githubusercontent.com/pytorch/pytorch/main/torch/utils/collect_env.py
# For security purposes, please check the contents of collect_env.py before running it.
python collect_env.py
l2002924700 commented 1 week ago

Hi @l2002924700, thank you for reporting this issue. To help us out, could you please run this script to give us more information about your system? thank you for ur kind answer

curl -O https://raw.githubusercontent.com/pytorch/pytorch/main/torch/utils/collect_env.py

results on my server:

% Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                Dload  Upload   Total   Spent    Left  Speed
100 24366  100 24366    0     0  17032      0  0:00:01  0:00:01 --:--:-- 17039

# For security purposes, please check the contents of collect_env.py before running it.
python collect_env.py
Collecting environment information...
PyTorch version: 2.3.0+cpu
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.4 LTS (x86_64) GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0 Clang version: 19.0.0 (++20240527042339+cbd8031baa62-1~exp1~20240527042438.1708) CMake version: version 3.29.3 Libc version: glibc-2.35

Python version: 3.10.0 (default, Mar 3 2022, 09:58:08) [GCC 7.5.0] (64-bit runtime) Python platform: Linux-5.15.0-122-generic-x86_64-with-glibc2.35 Is CUDA available: False CUDA runtime version: No CUDA CUDA_MODULE_LOADING set to: N/A GPU models and configuration: No CUDA Nvidia driver version: No CUDA cuDNN version: No CUDA HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True

CPU: Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 46 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 96 On-line CPU(s) list: 0-95 Vendor ID: GenuineIntel Model name: Intel(R) Xeon(R) Gold 5220R CPU @ 2.20GHz CPU family: 6 Model: 85 Thread(s) per core: 2 Core(s) per socket: 24 Socket(s): 2 Stepping: 7 CPU max MHz: 4000.0000 CPU min MHz: 1000.0000 BogoMIPS: 4400.00 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req pku ospke avx512_vnni md_clear flush_l1d arch_capabilities Virtualization: VT-x L1d cache: 1.5 MiB (48 instances) L1i cache: 1.5 MiB (48 instances) L2 cache: 48 MiB (48 instances) L3 cache: 71.5 MiB (2 instances) NUMA node(s): 2 NUMA node0 CPU(s): 0-23,48-71 NUMA node1 CPU(s): 24-47,72-95 Vulnerability Gather data sampling: Mitigation; Microcode Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Mitigation; Enhanced IBRS Vulnerability Spec rstack overflow: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Mitigation; TSX disabled

Versions of relevant libraries: [pip3] executorch==0.2.0a0+4f79832 [pip3] numpy==1.26.4 [pip3] nvidia-cublas-cu12==12.1.3.1 [pip3] nvidia-cuda-cupti-cu12==12.1.105 [pip3] nvidia-cuda-nvrtc-cu12==12.1.105 [pip3] nvidia-cuda-runtime-cu12==12.1.105 [pip3] nvidia-cufft-cu12==11.0.2.54 [pip3] nvidia-curand-cu12==10.3.2.106 [pip3] nvidia-cusolver-cu12==11.4.5.107 [pip3] nvidia-cusparse-cu12==12.1.0.106 [pip3] nvidia-nvjitlink-cu12==12.5.82 [pip3] nvidia-nvtx-cu12==12.1.105 [pip3] torch==2.3.0+cpu [pip3] torchao==0.1 [pip3] torchaudio==2.3.0+cpu [pip3] torcheval==0.0.7 [pip3] torchsr==1.0.4 [pip3] torchvision==0.18.0+cpu [conda] executorch 0.2.0a0+4f79832 pypi_0 pypi [conda] torch 2.3.0+cpu pypi_0 pypi [conda] torchaudio 2.3.0+cpu pypi_0 pypi [conda] torchvision 0.18.0+cpu pypi_0 pypi